Inequality and Privacy Rights

Despite the overwhelming potential of DL and its possible benefits,
it is still a “Disruptive” technology that is taking over operations
of the most advanced technology companies in the world.

Why is DL such a “disruptive” technology?
Why is DL taking over the most advanced tech.
companies in the world?

One can easily answer both of those questions by realizing that AI technologies could very possibly
lead to the next global arms race. Dylan Love, supports this idea as he writes about solutions
to solving the AI arms race in
The Next Global Arms Race Aims to Perfect AI
:

“Make AI development illegal,
but history suggests that prohibition doesn’t work.

Win the AI race.

Assemble an international AI consortium, with many nations pooling their resources.

Every nation unites under one flag and one leadership.”

Not a very promising list of options.

The threat of AI is not some futuristic idea, it is indeed here today and will become ever more sophisticated and controlling. Love however forgets to include a fifth option, solving the AI arms race in such a way that permits the sharing of AI across all of humanity. However until that happens, DL technology and DL expertise will be cornered by most of the world’s largest
technology companies completely monopolizing it and creating an increase in the gap between economic groups. Yoshua Bengio makes the following comments in a recent
Financial Times interview:

“Industry has been recruiting a lot of talent — there’s a shortage in academia. It’s fine for
those companies, but it’s not great for academia.”

“Even the big players talk about the tiny talent pool: Microsoft research chief Peter Lee says the cost of acquiring
a top AI researcher is comparable to the cost of acquiring an NFL quarterback.”

As a result, Deep Learning is thriving in many of these giant corporations who are therefore monopolizing the DL technology
and very possibly much of the resources, jobs, and control of our economic future.

These firms have made heavy investments in deep learning. Different organizations have their different priorities in what they believe is important. The likely winner of the AI race will be the
company that actually is lucky enough to have put resources into the winning approach! It is indeed very odd, given the high stakes involved, that there is an implicit gamble every firm is willing
to take to get a spot as the frontrunner in the AI market.

Unfortunately, for a majority of the world’s companies and population, most don’t
even know that the race exists! Even if they did know, just participating in the race has extremely low odds of success. Deep learning is reserved for the elite few and leading companies which will continue to guarantee that they will have the winning hand.
Deep learning needs to be democratized in order to create a more equitable global society. The problem is
best illustrated by the following video:

Our Inalienable Right to Privacy

The missing piece in almost every technology that has been created to ensure privacy is that it forces isolation and with
this comes the loss of access to AI capabilities. Future economy will give those with access to AI superior capabilities
over those who do not. If AI however is available only from the mega corporations and their business models are based on
us giving away our right to privacy then we are left between a rock and a hard place. Access AI but lose your right to privacy.
This clearly is unacceptable.

Intuition Fabric with its feature of decentralized ownership of AI permits us to keep our privacy while having access to the best Deep
Learning capabilities. This is because the code for the AI is a shared common good that is accessible from anywhere. A user can
thus execute the code in one’s private sandbox or can use trusted providers to execute code. Therefore revealing only the
minimal amount necessary to another party.

AI vs AI

When we interact with the world, we give away bits of our privacy every time. The effectiveness of the NSA’s ability to gather
valuable intelligence using only “meta-data” of phone records tells us that we need tools to protect us from this kind of
snooping. There are new tools that have been developed that are designed to obfuscate our tracks. A recent Wired article
“Wanna Protect your Online Privacy? Open a Tab and Make some Noise”) provides a glimpse of what is in the horizon. The tool
described in the article is rudimentary in that is selects random links. However, more sophisticated AI tools can be built
that don’t do this randomly, but actually mock human behavior. This is adversarial AI and this is a necessary capability
in the war to prevent our loss to privacy.